Volume 12, Number 1

Generating Software Product Line Model by Resolving Code Smells in the Products’ Source Code

  Authors

Sami Ouali, University of Technology and Applied Sciences, Oman

  Abstract

Software Product Lines (SPLs) refer to some software engineering methods, tools and techniques for creating a collection of similar software systems from a shared set of software assets using a common means of production. This concept is recognized as a successful approach to reuse in software development. Its purpose is to reduce production costs by reusing existing features and managing the variability between the different products with respect of particular constraints. Software Product Line engineering is the production process in product lines and the development of a family of systems by reusing core assets. It exploits the commonalities between software products and preserves the ability to vary the functionalities and features between these products. The adopted strategy for building SPL can be a top-down or bottom-up. Depending from the selected strategy, it is possible to face an inappropriate implementation in the SPL Model or the derived products during this process. The code can contain code smells or code anomalies. Code smells are considered as problems in source code which can have an impact on the quality of the derived products of an SPL. The same problem can be present in many derived products from an SPL due to reuse or in the obtained product line when the bottom-up strategy is selected. A possible solution to this problem can be the refactoring which can improve the internal structure of source code without altering external behavior. This paper proposes an approach for building SPL from source code using the bottom-up strategy. Its purpose is to reduce code smells in the obtained SPL using refactoring source code. This approach proposes a possible solution using reverse engineering to obtain the feature model of the SPL.

  Keywords

Software Product Line, Code smells, Refactoring, Reverse Engineering, Feature Model.